Holding cash is a losing strategy because governments consistently respond to economic crises by printing money. This devalues savings, effectively forcing individuals to invest in assets like stocks simply to protect their purchasing power against inflation.

The primary driver of wealth inequality isn't income, but asset ownership. Government money printing to cover deficit spending inflates asset prices. This forces those who understand finance to buy assets, which then appreciate, widening the gap between them and those who don't own assets.

Decades of currency debasement through money printing have made asset ownership essential for wealth preservation. Since a house is the most intuitive asset for the average person, owning one transformed from a component of the American Dream into a compulsory defense against inflation.

Most of an index's returns come from a tiny fraction of its component stocks (e.g., 7% of the Russell 3000). The goal of indexing isn't just diversification; it's a strategy to ensure you own the unpredictable "tail-event" winners, like the next Amazon, that are nearly impossible to identify in advance.

New technologies perceived as job-destroying, like AI, face significant public and regulatory risk. A powerful defense is to make the general public owners of the technology. When people have a financial stake in a technology's success, they are far more likely to defend it than fight against it.

During profound economic instability, the winning strategy isn't chasing the highest returns, but rather avoiding catastrophic loss. The greatest risks are not missed upside, but holding only cash as inflation erodes its value or relying solely on a paycheck.

In an unpredictable AI-driven job market, the most reliable path to financial security is not a specific skill but owning assets. This allows individuals to participate in the massive wealth generated by the technology itself, providing a hedge against inflation and potential job displacement, and avoiding a future of dependency on government assistance.

Recent events, including the Fed's interest rate cuts citing unemployment uncertainty and AI-driven corporate restructuring, show AI's economic impact is no longer theoretical. Top economists are now demanding the U.S. Labor Department track AI's effect on jobs in real-time.

Unlike past technological shifts where humans could learn new trades, AI is a "tractor for everything." It will automate a task and then move to automate the next available task faster than a human can reskill, making long-term job security increasingly precarious for cognitive labor.